#intend to able to zoom into country when choosing the country,default singapore
waste_type total_waste_generated_tonne
1 Construction & Demolition 1624000
2 Ferrous Metals 1269000
3 Paper/Cardboard 1054000
4 Plastics 949000
5 Food 763000
6 Wood/Timber 521000
total_waste_recycled_tonne year total_waste_not_recycled_tonne recycling_rate
1 1618000 2018 6 1.00
2 126000 2018 1143 0.10
3 586000 2018 468 0.56
4 41000 2018 908 0.04
5 126000 2018 637 0.17
6 428000 2018 93 0.82
wasting_rate
1 0.00
2 0.90
3 0.44
4 0.96
5 0.83
6 0.18# A tibble: 15 × 3
Material Total Waste Generate…¹ Total Waste Recycled…²
<chr> <dbl> <dbl>
1 Overall 131824000 75119000
2 Paper/Cardboard 23530000 11504000
3 Ferrous Metals 22414000 20472000
4 Construction & Demolition 22245000 21970000
5 Plastics 15797000 1280000
6 Food 13681000 1836000
7 Wood/Timber 6608000 4440000
8 Horticultural 5521000 3197000
9 Others (stones, ceramic, rubbe… 5426000 197000
10 Used Slag 5003000 4786000
11 Textile/Leather 2854000 199000
12 Non-Ferrous Metals 2094000 1865000
13 Glass 1413000 236000
14 Used slag 1366000 1347000
15 Scrap Tyres 502000 431000
# ℹ abbreviated names: ¹`Total Waste Generated (tonnes)`,
# ²`Total Waste Recycled (tonnes)`# A tibble: 15 × 3
waste_type total_waste_generated total_waste_recycled
<chr> <dbl> <dbl>
1 Overall 131824000 75119000
2 Paper/Cardboard 23530000 11504000
3 Ferrous Metals 22414000 20472000
4 Construction & Demolition 22245000 21970000
5 Plastics 15797000 1280000
6 Food 13681000 1836000
7 Wood/Timber 6608000 4440000
8 Horticultural 5521000 3197000
9 Others (stones, ceramic, rubber, … 5426000 197000
10 Used Slag 5003000 4786000
11 Textile/Leather 2854000 199000
12 Non-Ferrous Metals 2094000 1865000
13 Glass 1413000 236000
14 Used slag 1366000 1347000
15 Scrap Tyres 502000 431000 waste_type total_waste_generated_tonne
1 Construction & Demolition 1624000
2 Construction & Demolition 1440000
3 Construction & Demolition 825000
4 Construction & Demolition 1013000
5 Construction & Demolition 1424000
6 Construction & Demolition 1595000
total_waste_recycled_tonne year total_waste_not_recycled_tonne recycling_rate
1 1618000 2018 6 1.00
2 1434000 2019 6 1.00
3 822000 2020 3 1.00
4 1011000 2021 2 1.00
5 1419000 2022 5 1.00
6 1586000 2016 9 0.99
wasting_rate energy_saved crude_oil_saved
1 0.00 34644 96.00
2 0.00 252 0.72
3 0.00 1926 5.40
4 0.00 28000 80.00
5 0.00 20500 55.00
6 0.01 3600 9.90======================================================================= ### Chart E
#```{r} #scatter plot graph fig <- plot_ly( data = total_data, x = ~year, y = ~energy_saved, size = ~total_waste_generate_tonne, color = ~material, sizes = c(10, 60), type = “scatter”, mode = “markers” )
fig
annual_energy_savings <- total_data %>% group_by(year) %>% summarize(energy_saved = sum(energy_saved))
annual_energy_savings\(total_energy_saved <- round(annual_energy_savings\)energy_saved / 1000000, 2)
tail(annual_energy_savings) ```